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Automated Analysis of EIT Data for PEEP Setting

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ClinicalTrials.gov Identifier: NCT03653806
Recruitment Status : Recruiting
First Posted : August 31, 2018
Last Update Posted : February 20, 2020
Sponsor:
Collaborators:
University of Schleswig-Holstein
Erasmus Medical Center
Information provided by (Responsible Party):
Maastricht University Medical Center

Brief Summary:

First: to develop a computerized algorithm for automated analysis of the electrical impedance tomography (EIT) data. The algorithm calculates the "optimal" positive end-expiratory pressure (PEEP) and inspiratory pressure defined as the "optimal" balance between stretch, ventilation distribution and collapse.

Second: to compare the results of the algorithm with the current standard of care clinical judgement of an experienced ventilation practitioner.


Condition or disease Intervention/treatment
Acute Hypoxemic Respiratory Failure Post-cardiac Surgery Other: computerized algorithm for automated analysis

Detailed Description:

The study will be performed at the Intensive Care Unit, Maastricht University Medical Centre. The investigators routinely apply EIT (Pulmovista, Dräger, Lübeck. Germany) in mechanically ventilated patients to optimize the ventilator settings .

An algorithm will be developed by the Institute of Technical Medicine, Furtwangen University, Germany. The algorithm will automatically detect changes in both PEEP and inspiratory pressures. For each PEEP step and/or changes in inspiratory pressure the difference in regional alveolar overdistension and alveolar collapse will be calculated. This makes it possible to select the optimal ventilator setting depending on the best compromise between alveolar overdistension and alveolar collapse.

The algorithm will be tested in 40 EIT guided mechanically ventilated patients. EIT measurements will be performed during an incremental and decremental PEEP trial. The EIT measurement will be performed in the same way as during standard clinical care. EIT data will be analysed offline by a ventilation practitioner with experience in EIT and with the newly developed algorithm. The resulting advice on optimal ventilator settings will be compared for inter-observer variability.

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Study Type : Observational
Estimated Enrollment : 40 participants
Observational Model: Other
Time Perspective: Prospective
Official Title: Comparing the Results of a Computer Analysis Algorithm With Clinical Decisions in a Patient With Electrical Impedance Tomography Guided Ventilator Settings Regarding Optimal Positive End Expiratory Pressure and Inspiratory Pressure
Actual Study Start Date : November 21, 2017
Estimated Primary Completion Date : May 31, 2020
Estimated Study Completion Date : May 31, 2021

Intervention Details:
  • Other: computerized algorithm for automated analysis

    First: to develop a computerized algorithm for automated analysis of the electrical impedance tomography (EIT) data. The algorithm calculates the "optimal" positive end-expiratory pressure (PEEP) and inspiratory pressure defined as the "optimal" balance between stretch, ventilation distribution and collapse.

    Second: to compare the results of the algorithm with the current standard of care clinical judgement of experienced EIT users



Primary Outcome Measures :
  1. develop automated EIT data algorithm for PEEP setting [ Time Frame: 4 months ]
    The automated algorithm will give an advise on PEEP and delta pressure settings, based upon the EIT data, which is in accordance with the decision of the investigator



Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
Post cardiac- surgery and patients with acute hypoxic respiratory failure
Criteria

Inclusion Criteria:

  • Mechanically ventilated in a volume or pressure controlled mode
  • ventilator settings guided by EIT

Exclusion Criteria:

  • Participants who specifically opt-out regarding the use of the data for research purpose
  • Internal pacemaker, Implantable Cardioverter Defibrillator
  • Skin lesions, dressings at the thorax, hindering belt placement
  • Thoracic circumference < 70 cm
  • Thoracic circumference > 150 cm
  • BMI > 50

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03653806


Contacts
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Contact: Serge Heines +31433876385 s.heines@mumc.nl

Locations
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Netherlands
Serge Heines Recruiting
Maastricht, Netherlands, 622HX
Contact: Serge Heines    +31433876385    s.heines@mumc.nl   
Sponsors and Collaborators
Maastricht University Medical Center
University of Schleswig-Holstein
Erasmus Medical Center
Investigators
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Study Chair: Dennis Bergmans Maastricht University Medical Center

Publications:
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Responsible Party: Maastricht University Medical Center
ClinicalTrials.gov Identifier: NCT03653806    
Other Study ID Numbers: 17-4-053
First Posted: August 31, 2018    Key Record Dates
Last Update Posted: February 20, 2020
Last Verified: February 2020
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by Maastricht University Medical Center:
PEEP
Electrical Impedance Tomography
Additional relevant MeSH terms:
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Respiratory Insufficiency
Respiration Disorders
Respiratory Tract Diseases